Development of Expert System for Selecting Tomato (solanum lycopersicum L.) Varieties

The increasing number of tomato varieties with their unique features, has introduced greater subjectivity and complexity for selection of tomato varieties. This study developed Expert System Selection of Tomato Varieties (SIPMAT) to assist dissemination of knowledge related to the selection of tomato varieties. This system was also developed to help farmers to determine varieties that match with some parameters or user preferences. This expert system used 135 tomato varieties. Inference engine developed on the expert system using Tahani fuzzy logic rules combined with Simple Additive Weighting (SAW) as weighting rules. There are 9 parameters used for selection in the system including planting goals, altitude, resistance to diseases, fruit size, fruit shape, hardness, yield potential, maturity and fruit color with weight of each parameter according to experts and farmer preferences. The prototype was developed on web using PHP programming language and MySql for data base management system. The system was tested and it showed the accuracy of 86.2%.